People

Huiming Ding, Toufighi, Judice Koh

In SGA, identification of genetic interactions is based on double mutant fitness which is assessed as a measure of colony size. In order to meet our throughput demands, we have designed and developed an automated, quantitative approach to score fitness. This computational platform facilitates large-scale SGA data analysis and provides an analysis pipeline consisting of the following steps: image processing, fitness scoring, data storage, statistical analysis and data mining (Fig.4).

Several laboratories around the world have implemented this system and actively contribute data to our growing repository, the Genetic Interaction Database (GID).